The use of satellites for the transmission of voice and data communication signals has greatly expanded over the past decade, and satellite links are now routinely used and relied upon for global, almost instant, bidirectional communications. Rapid improvements in satellite communications have produced beneficial impacts on many segments of society from business and commercial applications to consumer products. For example, residences throughout the world now receive news and entertainment broadcasts via satellite, in nearly real-time from sites in almost any country.
Burst-mode communication systems and the related synchronization techniques are frequently used in satellite voice and data receivers. These systems typically employ multiple transmitters that send “bursts” of transmissions to a receiver to provide multiple access to many users. Bursts from the different transmitters are coordinated in time and frequency such that each transmitter can communicate with the receiver without interfering with each other. In one type of burst-mode communication, Time Division Multiple Access (TDMA) allows multiple users to share a single carrier wave using time-division multiplexing (TDM) to transmit multiple bursts on that carrier wave. TDM divides the carrier wave into time slots and then allocates those time slots to the different data signals. Effectively, each of the data signals takes turns accessing the carrier wave, thereby allowing a single carrier wave to carry multiple simultaneous data transmission. A Multi-Frequency Time Division Multiple Access (MF-TDMA) receiver simultaneously receives TDMA signals on several different carrier frequencies. In the MF-TDMA data transmission scheme, any user can potentially transmit data at any frequency at any time. The actual time slot and frequency allocation to each user is based on capacity requests submitted by the terminal.
Within the TDMA bursts specified in DVB-RCS Standard, the carrier signal is modulated by data symbols in which a phase characteristic of the symbol represents the data. This type of modulation technique is known as “phase shift keying” (PSK) data modulation. In general, each symbol can be represented as a phasor in which the phase state of the symbol at the correct detection interval, or the relative change in phase from symbol to symbol, represents data. This data, in turn, can be expressed as a corresponding bit or combination of bits in which the number of bits corresponds to the number of possible phase states used for data modulation. For example, in binary phase shift keying (BPSK), each symbol may have one of two phase states (i.e., 0, π). Each BPSK symbol can therefore represent a single binary digit (bit). In quadrature phase shift keying (QPSK), each symbol may have one of four phase states (i.e., 0, π/2, π and 3π/2). Each QPSK symbol can therefore represent two binary digits. In the general “M” phase shift keying (MPSK), each symbol may have “M” phase states. Each MPSK symbol can therefore represent “n” binary digits, where M=2n.
Typically, MF-TDMA signals are de-multiplexed and re-arranged to form a signal equivalent to a single carrier. The single-carrier data signal is then demodulated to recover the underlying data (transmitted information bits). The demultiplexing and demodulation steps are well known in the field of communications and are the subject of extensive research and development to improve transmission speeds, bandwidth, accuracy, and reliability.
Several satellite data transmission standards have been adopted to harmonize the transmission and reception of satellite communications broadcasts. One known standard adopted in the broadcast of Digital Video Broadcast (DVB) signals is Digital Video Broadcast by Satellite (DVB-S). Standard EN 300 421 of the ETSI (European Telecommunications Standards institute). This standard relates to DVB services and transparent satellite communication systems to provide DVB-S services directly to the user through an integrated receiver/decoder device that is located in the user's home: The versatility of DVB-S in multiplexing permits the use of a transmission capacity encompassing a variety of television service configurations, including sound and data services.
The components of the DVB-S services are transmitted on a TDM carrier wave. For more information on the DVB-S standard, please refer to ETSI publication EN 300 421 V1.1.2 (1997-98), entitled “Digital Video Broadcasting (DVB); Framing structure, channel coding and modulation for 11/12 GHz satellite services,” the subject matter of which is hereby incorporated herein by reference.
Satellite broadcasts are also increasingly used for instantaneous two-way audio, video, and data communications. Accordingly, recent attention has been given to the demand for making satellite communications interactive so that recipients of the broadcast can also communicate back to the origin of the transmission. For example, satellite communications can be used to provide Internet connections between different users. In an effort to establish unified bi-directional satellite communications, the digital video broadcast with return channel by satellite (DVB-RCS) standard has been enacted by the ETSI.
The DVB-RCS standard relates to interaction channels on a satellite distribution system. The purpose of this standard is to provide basic specifications for providing interaction channels for interactive networks based on geostationary (GEO) satellites that incorporate return channel satellite terminals (RCST). The DVB-RCS standard facilitates the use of RCSTs for domestic installations both individual and collective types. The DVB-RCS standard likewise supports the connection of the terminals with home data networks, and can be applied to all frequency bands allocated to GEO satellite services. For more information on the DVB-RCS standard, refer to ETSI publication, EN 301 790 v.1.3.1, dated 2003-03, entitled “Digital Video Broadcasting (DVB); Interaction Channel for Satellite Distribution Systems,” the subject matter of which is hereby incorporated herein by reference.
Satellite communication systems operating under the DVB-RCS standard can exchange data using a variety of network and Internet technologies. For example, the DVB-RCS standard accommodates Asynchronous Transfer Mode (ATM) technology for transferring data in cells or packets of a fixed size. The data packet used with ATM is relatively small compared to packets used with older technologies. The small, constant packet size allows ATM equipment to transmit video, audio, and computer data over the same network, and assures that no single type of data hogs the line. ATM creates a fixed channel, or route, between two points whenever data transfer begins, unlike TCP/IP that divides messages into packets that can each take a different route from source to destination. Consequently, it is generally easier to track and bill data usage across the ATM network, but the ATM network is less adaptable to sudden surges in network traffic. Similarly, the DVB-RCS standard may be used to transmit MPEGs (Moving Picture Experts Group), a family of digital video compression standards and file formats that achieve high compression rate by storing only the changes from one frame to another, instead of each entire frame.
Loss of bursts (or packets), as measured by packet loss ratio, is a main performance criterion for evaluating the burst-mode data transmission. The typical expected packet loss ratio for traffic bursts over return satellite link is 10−7 (i.e., one lost packet in ten million). Due to a long propagation delay in Geostationary satellite communications, the packet loss ratio should be low in order to avoid performance degradation at higher network layers. The human senses are generally tolerant of slight variations, so for the transmission of video and sound broadcasts, as defined by DVB-RCS, the packet loss ratios is preferably in the order of 1×10−5, so that less than one packet is lost per hundred-thousand burst-mode signals.
One way to decrease packet loss is to increase signal transmission strength or effective isotropic radiated power (EIRP) of the transmitter, thereby increasing the signal-to-noise ratio at the receiver. Improvements in the signal-to-noise ratio are desirable because, as provided by Shannon's theorem, the ultimate theoretical limit to the data transmission transfer rate on a communications channel is directly proportional the signal-to-noise ratio of that channel. Consequently, increasing the power transmitted on the return channel can often be a solution to provide adequately reliable communications. However, increasing the transmission power requires the use of more sophisticated equipment, which in turn increases unacceptably the cost of the transmitter. Accordingly, there is a current need for a demodulation technology that allows reliable burst-mode communications at relatively poor channel conditions (low signal-to-noise ratio). More specifically, there is a current need for a demodulation technology that allows for reliable burst-mode data transmission in a DVB-RCS system with sufficiently low packet loss ratio while maintaining or even reducing current terminal transmission power levels in order to minimize the cost of user terminals.
Another important aspect of DVB-RCS system application is the provision of services at Ka-band frequencies (e.g., 30 GHz uplink from terminals to satellite). The cost of user terminal plays a major role in the business model of this type of services. RF components of the terminals are costly. Less expensive RF components results in tighter link budget on the uplink from the terminal to satellite. For such users the use of very power efficient modems is essential in order to maintain acceptable level of system availability.
Thus, there exist a further need for a demodulating technology that allows for sufficiently low packet loss ratio for DVB-RCS transmissions with higher power efficiency. As suggested above, numerous technical and physical problems complicate the synchronization in satellite communications. For instance, the synchronization may be difficult where the transmitter and receiver are moving relative to each other. Specifically, when a burst-mode communication transmitter is on or near the earth and the intended receiver is in a satellite (or when a satellite transmits to the terrestrial receiver), the spatial locations and the relative velocities of the transmitter and receiver change over time. The change in spatial location causes the propagation path length and the signal propagation time to change, and the change in relative velocities causes a Doppler frequency to change the frequency of the burst-mode signal when it is received at the intended receiver. As a consequence, the burst-mode signals, originally transmitted at fixed intervals, arrive at varying time intervals. Furthermore, varying weather conditions, such as clouds and rain, also affect the communication signals. There is also certain level of inherent carrier frequency uncertainty at the transmitter output. Overall, these and other conditions cause carrier frequency offset in the burst-mode communication.
These issues are particularly present in DB-RCS communications at Ka band. At a DVB-RCS transmitter output, a 30 GHz carrier will generally appear with some carrier frequency offset fo, or residual error, so that carrier frequency (fc)=30 GHz±fo. The DVB-RCS Standard puts a constraint on the uncertainty in carrier frequency at the output of the transmitter. According to the DVB-RCS Standard, the normalized carrier frequency accuracy should be better than 10−8. The accuracy is defined in terms of root-mean square error. Carrier frequency variation can be up to 6 times this value. For example, for a Ka band transmitter at 30 GHz carrier, the carrier frequency offset can be in the range of ±1800 Hz (30×109 Hz×10−8×6=1800 Hz).
In addition to the frequency uncertainty caused by the terminal, contributors to the carrier frequency offset include: movement of the satellite (creating Doppler effect), uncertainty due to the satellite's transponder, uncertainty or changes at the transmitter as to the exact carrier frequency, and length and atmospheric conditions en route. These and other contributors in the system deviate the carrier off its nominal value and synchronization is performed to correct for the carrier frequency offset and get the carrier back to its nominal or baseband state. In a sense, synchronization is a fine-tuning value for best receiver performance.
Accordingly, the synchronization process generally includes burst detection, finding the right sampling timing (i.e., the symbol timing), finding the carrier frequency offset, and tracking the carrier phase. After the right combination of these factors is determined, thereby establishing synchronization, then the coherent data symbols of a burst are passed to a decoder to extract and deliver the payload data in the that burst.
Accordingly, in synchronous digital transmission, information is conveyed by uniformly spaced pulses and the function of any receiver is to isolate these pulses as accurately as possible. However, the received signal has undergone changes during transmission due to the noisy nature of the transmission channel, and a complete estimation of certain reference parameters is necessary prior to data detection. Estimation theory proposes various techniques for estimating these parameters depending on what is known of their characteristics. One such technique is called maximum likelihood (ML) estimation. Maximum likelihood estimation assumes the parameters are deterministic or at most slowly varying over the time interval of interest. The term deterministic implies the parameters are unknown but of a constant value and are, therefore, not changing over the observation interval. These unknown parameters can cover such factors as the optimum sampling time, the static phase offset, or carrier frequency offset introduced in the channel or induced by the instabilities of the transmitter and receiver oscillators. It is widely recognized that maximum likelihood estimation techniques offer a systematic and conceptually simple guide to the solution of synchronization problems. Maximum likelihood provides (near) optimum performance depending on the known channel. However, for a general parameter estimation problem, the Maximum likelihood estimator may not exist or the structure of the Maximum Likelihood estimator can be too complex to be implemented in practical systems. In many cases, practical estimators are derived as an approximation of Maximum Likelihood parameter estimators. See, for example, J. G. Proakis, “Digital Communications,” Third Edition, McGraw-Hill Publishers, 1995, pp. 333-336.
Synchronization techniques used in communication receivers are typically derided from Maximum Likelihood estimators. For communication receivers, there exist two categories of the parameter estimators, depending on how the data present on the received signal is exploited to assist in parameter estimation. The first is data-aided (DA) parameter estimation, in which known data structure within the received signal is exploited. In DA parameter estimation, known data symbols, such as symbols in the signal header or preamble, are identified and then used to reduce the ambiguity of signal observation in order to obtain more accurate estimation of the desired parameter (e.g., carrier frequency offset, phase offset, symbol timing, etc.). Numerous DA estimation techniques are known. For example, U. Mengali, M. Morelli, Data-Aided Frequency Estimation for Burst Digital Transmission, IEEE Transaction On Communications, Vol. 45, No. 1, January 1997, pp 23-25, introduce a data-aided frequency estimator for burst-mode phase-shift keying (PSK) signals.
Alternatively, non-data-aided (NDA) estimation techniques form parameter estimations without relying on underlying data of modulated signal. NDA estimation is generally possible when the random data is considered a nuisance parameter, which is removed by averaging the received signal over the statistics of the random data. For example, Morelli and Mengali (M. Morelli, U. Mengali, “Feed-forward carrier frequency estimation with MSK-type signals,” IEEE Communications Letters, no. 8, August 1998 pp. 235-237) describes a NDA technique for the carrier frequency offset estimation of a minimum-shift keying (MSK)-type modulated signal. The algorithm proposed by Morelli and Mengali has a feedforward structure and is suited for burst-mode transmissions, as described herein. It should be appreciated that numerous NDA parameter estimation techniques for modulated signals are known.
These known parameter estimation techniques usually operate at relatively high signal-to-noise ratio that allow reliable estimates. A proper synchronization of a burst-mode signal is needed to reacquire the transmitted data. In particular, the known burst-mode signal demodulation techniques perform synchronization and then the decoding. As a consequence, the receiver generally includes a cascade of components including a receiving filter, a synchronizer, and a decoded to process received burst-mode signals. Iterative decoding schemes for turbo-coded signals have made it possible to improve the power efficiency of the transmission. However, at low signal-to-noise level, the full coding gain is not achievable due to carrier synchronization errors. For example, in a DVB-RCS return link with short burst size and low coding rate, the error caused by the carrier synchronization degrades the performance significantly. Since the return channel is operating at a very low signal-to-noise ratio, carrier synchronization based on traditional approach cannot alone give the accurate synchronization that is needed for reliable decoding.
A data-aided parameter estimator alone is unable to provide accurate estimate mainly because the number of pilot symbols transmitted in each burst is small. It is desirable to maintain the number of pilot symbols as small as possible since they do not carry any information and are considered as overhead. The non-data aided estimator can potentially use all symbols (pilot symbols and data symbols) for parameter estimation. For a moderate or high level of signal-to-noise, an NDA estimator provides a better performance than a DA estimator since the length of data-symbols is typical many times larger than the number of pilot symbols. However, at low signal-to-noise level, the performance of the NDA estimator is significantly degraded.
The currently known techniques for parameter estimations generally fail to provide reliable estimate when signal-to-noise level is below certain threshold. When falling below the threshold value, the conventional algorithms fail to operate properly. The threshold level depends on the size of data symbols, the type of modulation and the range of the parameter. Unfortunately, the threshold level for frequency estimation of QPSK modulated burst-mode signals can be higher than the operating signal-to-noise level. Much of the current research and development (so far unsuccessful) is directed toward developing techniques to reduce this threshold level.
Theoretical studies can be conducted on existing frequency estimators to determine their fundamental performance level. Such fundamental performance bounds are typically expressed in terms of the mean square error (MSE) of the estimate. It can be shown that the threshold effect of frequency estimate is fundamental. As a result, it is not expected that a conventional DA or NDA frequency estimator be able to provide the accuracy that is required for frequency estimation of QPSK burst-mode signals at low signal-to-noise level.
As a result, there is an on-going need for techniques and systems for detecting and correcting for signal distortion, such as the carrier frequency offset that typically occurs in a burst-format satellite communication systems operating at low signal-to-noise ratio.